Duke FINTECH Trading Competition 2021

The Duke FINTECH Trading Competition is a free competition hosted by the FINTECH Program at Duke University.

The Competition is open to any currently enrolled graduate or undergraduate student with a .edu address. As posted in the Official Announcement, the winner of the competition will be awarded a $2,000 cash prize!

Participants are granted paper trading accounts at Interactive Brokers, which enable them to trade equities, options, ETFs, futures, currencies, bonds, and more, all based on real-time streaming market data. Students use the same execution systems as professional traders IBKR’s Mobile App, Trader Workstation GUI and IB Gateway) – the only difference is that the money they trade is simulated.

The Spring 2021 session is currently underway. We are pleased that about 90 students at various universities have signed up for this session, which is the very first offering of the competition outside of Duke.

The Duke FINTECH Department is striving to be as inclusive and welcoming as possible to all students, and will be reaching out again next Fall for the next offering. Participation is welcome and encouraged, so please help spread the word for future semesters!

Standings for the top 10 traders will be posted here and updated daily. This site will continue to grow as new features are brought onboard. Be sure to check back often for updates!!!

The competition started on 11 Mar 2021 and will conclude on 07 May 2021.

Standings

The information on this page was last refreshed on 2021-05-09 17:19:38. At that time, the data was available for the range from 2021-03-11 to 2021-05-07.

Standings are updated based on the data available at the time of the update. It takes time for students’ account balances to be brought current – results are usually available for the previous trading day at or after approximately 6PM EST on the next trading day.

Top Sharpe Ratios (competition standings)

Participants are scored by their Sharpe Ratios. Current standings are:
Top 10 Sharpe Ratios
Ranking Trader School Daily Excess Return Daily Vol Sharpe Ratio
1 TradeBroker Duke 0.00154% 0.00481% 0.320
2 nonFortissimus UNC Chapel Hill 0.00069% 0.00338% 0.203
3 Joe_Shmoe NC State 0.00077% 0.00382% 0.202
4 endtimes NC State 0.00151% 0.00782% 0.193
5 Mfmurray NC State 0.00142% 0.01062% 0.133
6 Stark NC State 0.00026% 0.00224% 0.114
7 Beautylun Duke 0.0084% 0.07432% 0.113
8 bw98 Duke 0.00034% 0.00471% 0.071
9 Wall Street Legend Wake Forest 0.04575% 0.82761% 0.055
10 Rot00 NC State 0.00066% 0.01264% 0.053

Top 10 Daily Excess Returns

Calculated as the geometric mean of daily excess returns. Included for bragging rights :).

Top 10 Excess Returns
Ranking Trader School Daily Excess Return Daily Vol Sharpe Ratio
1 Wall Street Legend Wake Forest 0.04575% 0.82761% 0.055
2 Not_A_Cat NC State 0.02902% 0.84427% 0.034
3 Beautylun Duke 0.0084% 0.07432% 0.113
4 TradeBroker Duke 0.00154% 0.00481% 0.320
5 endtimes NC State 0.00151% 0.00782% 0.193
6 Mfmurray NC State 0.00142% 0.01062% 0.133
7 Joe_Shmoe NC State 0.00077% 0.00382% 0.202
8 nonFortissimus UNC Chapel Hill 0.00069% 0.00338% 0.203
9 Rot00 NC State 0.00066% 0.01264% 0.053
10 NC State 0.00045% 0.01496% 0.030
#> [1] "All accounts are up to date."

Test purposes only:

# Source: http://www.htmlwidgets.org/showcase_plotly.html
library(plotly)
#> Loading required package: ggplot2
#> 
#> Attaching package: 'plotly'
#> The following object is masked from 'package:ggplot2':
#> 
#>     last_plot
#> The following object is masked from 'package:stats':
#> 
#>     filter
#> The following object is masked from 'package:graphics':
#> 
#>     layout
p <- ggplot(data = diamonds, aes(x = cut, fill = clarity)) +
            geom_bar(position = "dodge")
ggplotly(p)